Stream Compute Service is a powerful enterprise-grade real-time big data analytics platform based on Apache Flink. It features one-stop development, seamless connection, sub-second latency, low costs, high security, and high stability, helping businesses maximize the value of their data and accelerate their move to real-time data processing.
Stream Compute Service
A Flink-based streaming data aggregation and computing service.
Benefits
One-Stop Development
Provide one-stop development and Ops via Web IDE or Tencent Cloud API. Support multi-language graphical development, metadata, dependency, deployment management, code debugging, operation monitoring, metric alerting, and intelligent diagnosis.
Seamless Connection
Seamlessly integrate with Tencent Cloud’s core data services (message queue, database, data warehouse) and self-deployed open-source big data components. Expand connectors to access diverse external data systems on demand, and deliver full compatibility with Apache Flink for smooth cloud migration.
Sub-Second Latency
Process 100,000+ records per second per CPU core with end-to-end latency under 1 second, and sustain tens of thousands of concurrent large-scale real-time computing tasks.
Low Costs
Leverage industry-leading proprietary server technology and load-based resource allocation to cut per-core computing costs to just a few cents per hour—far more cost-effective than self-deployed framework.
High Security and Stability
Isolate resource environments by space and process, and ensure tenant data security with fine-grained access control from the Tencent Cloud account system. Achieve second-level failover to guarantee 99.9% SLA.
Expert Service
Access end-to-end solutions and 24/7 operational support from the Tencent Cloud expert team.
Scenarios
Gaming
Finance
Ecommerce
Manufacturing
Education
The boom of the mobile internet has driven the unprecedented expansion of the gaming industry. As new game categories and genres continue to emerge, game vendors are putting more and more focus on improving user engagement through refined data operations. Stream Compute Service helps them perform refined data analysis in real time.
The finance industry is becoming increasingly integrated with the internet. Stream Compute Service enables big data analysis that provides more comprehensive marketing, monitoring, reporting, risk management, and profiling across all links in the finance industry.
The ecommerce industry is inherently closely integrated with the internet, generating vast amounts of data related to customers, merchants, and supply chains. The mining and analysis of ecommerce data helps service providers quickly match their products with customers, optimize their supply chains, and enhance their warehousing capabilities. Stream Compute Service enables businesses to analyze big data in real time.
The traditional manufacturing industry generates huge amounts of data in production, quality inspection, management, and sales processes, much of which goes ungoverned and unused. Big data analytics applications for real-time monitoring, scheduling, alarming, and smart data analytics can enhance the production efficiency of traditional manufacturing and enable timely detection of production defects. Stream Compute Service empowers Industry 4.0 with its powerful real-time analytics capabilities.
The education industry has a natural need for refined data analytics. Real-time big data analytics can help educators accommodate the unique characteristics of each student and provide personalized teaching more efficiently.
Pricing
To use Stream Compute Service, you need to purchase a cluster where each Compute Unit (CU) consists of 1 CPU core and 4 GB of memory; a management node fee equivalent to 2 CUs applies (waived for 48+ CUs), and billing rules for configuration adjustments like capacity expansion and renewal align with initial purchase terms. For details, refer to Billing Overview.
Help and Documentation
FAQs
What is a CU?
What is real-time stream data?
What are the strengths of stream computing over batch computing?
Can the JAR job mode be connected to self-built services?
What are fine-grained resources?